Comprehensive pressure profiling to develop next-generation compression treatment for lymphedema: Testing efficacy of high resolution sensors

摘要

Evidence for the use and effectiveness of compression garments (sleeves, stockings) for medical conditions including lymphedema and deep vein thrombosis remains empirical. The contemporary mandate for evidence-based medical practices, i.e. the delivery of care based on objective, effective measurements (efficacy), gives impetus for the establishment of both standardized testing protocols and tools enabling accurate spatial and temporal measurements of pressures delivered by compression garments. This study proposes the establishment of Gage Linearity and Bias study protocols to assess efficacy of pressure testing sensors within and between studies. While several such sensors are commercially available, they have not been tested in clinically relevant pressure ranges or contexts. The efficacy of a current commercial, high-resolution and compliance pressure sensor (Tekscan 9833E Medical Sensor) was assessed using Gage Linearity and Bias methods. The Tekscan sensor proved insufficient for the accurate measurement of target pressure ranges applied by lymphedema compression sleeves. The study demonstrates that standardization, and the use of protocol techniques such as the adapted Gage Linearity and Bias methods presented here, lend themselves well for efficacy testing of pressure sensing technologies. Further, this study highlights efforts underway to develop customized sensors and technologies enabling efficacy testing of compression treatments in situ in patients and in age-matched, healthy control subjects. Effective high resolution pressure sensors will enable comprehensive pressure profiling for establishment of efficacy-based compression treatments. Ultimately, effective high resolution pressure sensors will pave the way to elucidate mechanisms underpinning compression treatment and the etiology of lymphedema per se, a poorly understood condition with no current cure. (C) 2019 Published by Elsevier B.V.